Institute for Human-Centered Artificial Intelligence (HAI)


Showing 231-240 of 244 Results

  • Terry Winograd

    Terry Winograd

    Professor of Computer Science, Emeritus

    BioProfessor Winograd's focus is on human-computer interaction design and the design of technologies for development. He directs the teaching programs and HCI research in the Stanford Human-Computer Interaction Group, which recently celebrated it's 20th anniversary. He is also a founding faculty member of the Hasso Plattner Institute of Design at Stanford (the "d.school") and on the faculty of the Center on Democracy, Development, and the Rule of Law (CDDRL)

    Winograd was a founding member and past president of Computer Professionals for Social Responsibility. He is on a number of journal editorial boards, including Human Computer Interaction, ACM Transactions on Computer Human Interaction, and Informatica. He has advised a number of companies started by his students, including Google. In 2011 he received the ACM SIGCHI Lifetime Research Award.

  • Jiajun Wu

    Jiajun Wu

    Assistant Professor of Computer Science

    BioJiajun Wu is an Assistant Professor of Computer Science at Stanford University, working on computer vision, machine learning, and computational cognitive science. Before joining Stanford, he was a Visiting Faculty Researcher at Google Research. He received his PhD in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology. Wu's research has been recognized through the AFOSR Young Investigator Research Program (YIP), the ACM Doctoral Dissertation Award Honorable Mention, the AAAI/ACM SIGAI Doctoral Dissertation Award, the MIT George M. Sprowls PhD Thesis Award in Artificial Intelligence and Decision-Making, the 2020 Samsung AI Researcher of the Year, the IROS Best Paper Award on Cognitive Robotics, and faculty research awards from JPMC, Samsung, Amazon, and Meta.

  • Lei Xing

    Lei Xing

    Jacob Haimson and Sarah S. Donaldson Professor and Professor, by courtesy, of Electrical Engineering

    Current Research and Scholarly Interestsartificial intelligence in medicine, medical imaging, Image-guided intervention, molecular imaging, biology guided radiation therapy (BGRT), treatment plan optimization

  • Daniel Yamins

    Daniel Yamins

    Assistant Professor of Psychology and of Computer Science

    Current Research and Scholarly InterestsOur lab's research lies at intersection of neuroscience, artificial intelligence, psychology and large-scale data analysis. It is founded on two mutually reinforcing hypotheses:

    H1. By studying how the brain solves computational challenges, we can learn to build better artificial intelligence algorithms.

    H2. Through improving artificial intelligence algorithms, we'll discover better models of how the brain works.

    We investigate these hypotheses using techniques from computational modeling and artificial intelligence, high-throughput neurophysiology, functional brain imaging, behavioral psychophysics, and large-scale data analysis.

  • Seema Yasmin

    Seema Yasmin

    Clinical Assistant Professor, Medicine - Primary Care and Population Health

    BioSeema Yasmin is an Emmy Award-winning journalist, poet, medical doctor and author. Yasmin served as an officer in the Epidemic Intelligence Service at the U.S. Centers for Disease Control and Prevention where she investigated disease outbreaks and was principal investigator on a number of CDC studies. Yasmin trained in journalism at the University of Toronto and in medicine at the University of Cambridge.

    Yasmin was a finalist for the Pulitzer Prize in breaking news in 2017 with a team from The Dallas Morning News and recipient of an Emmy for her reporting on neglected diseases. She received two grants from the Pulitzer Center on Crisis Reporting. In 2017, Yasmin was a John S. Knight Fellow in Journalism at Stanford University investigating the spread of health misinformation and disinformation during epidemics. Previously she was a science correspondent at The Dallas Morning News, medical analyst for CNN, and professor of public health at the University of Texas at Dallas.

    She is the author of five books including What the Fact?! Finding the Truth in All the Noise (Simon and Schuster, 2022); Viral BS: Medical Myths and Why We Fall For Them (Johns Hopkins University Press, 2021) and Muslim Women Are Everything: Stereotype-Shattering Stories of Courage, Inspiration and Adventure (HarperCollins, 2020). Her writing appears in The New York Times, WIRED, Scientific American and other outlets.

    Yasmin’s unique expertise in medicine, epidemics and journalism has been called upon by the Vatican, the Presidential Commission for the Study of Bioethical Issues, the Aspen Institute, Skoll Foundation and others.

  • Serena Yeung

    Serena Yeung

    Assistant Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering

    BioDr. Serena Yeung is an Assistant Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering at Stanford University. Her research focus is on developing artificial intelligence and machine learning algorithms to enable new capabilities in biomedicine and healthcare. She has extensive expertise in deep learning and computer vision, and has developed computer vision algorithms for analyzing diverse types of visual data ranging from video capture of human behavior, to medical images and cell microscopy images.

    Dr. Yeung leads the Medical AI and Computer Vision Lab at Stanford. She is affiliated with the Stanford Artificial Intelligence Laboratory, the Clinical Excellence Research Center, the Center for Artificial Intelligence in Medicine & Imaging, the Center for Human-Centered Artificial Intelligence, and Bio-X. She also serves on the NIH Advisory Committee to the Director Working Group on Artificial Intelligence.

  • Greg Zaharchuk

    Greg Zaharchuk

    Professor of Radiology (Neuroimaging and Neurointervention)

    Current Research and Scholarly InterestsImproving medical image quality using deep learning artificial intelligence
    Imaging of cerebral hemodynamics with MRI and CT
    Noninvasive oxygenation measurement with MRI
    Clinical imaging of cerebrovascular disease
    Imaging of cervical artery dissection
    MR/PET in Neuroradiology
    Resting-state fMRI for perfusion imaging and stroke